Presenting our Inspire Challenge 2017 finalists
The CGIAR Platform Big Data in Agriculture has selected the finalists for five USD100K grants to be awarded during the inaugural convention 19-22 of September.
We are proud to present the 12 finalists to participate in the final round of the CGIAR Big Data in Agriculture Inspire Challenge 2017.
Finalists will present their proposals to judges during our CGIAR Big Data in Agriculture Convention 2017 on September 19-22, and five successful proposals will be awarded U$100K to develop their projects.
We received more than 120 proposals across the four Inspire Challenge Categories: Revealing Food Systems, Monitoring Pests and Diseases, Disrupting Impact Assessment, and Empowering Data-Driven Farming from applicants all over the world.
In a plenary session on Thursday the 21st of September, Inspire Challenge finalists will make the final presentation of their idea and have a brief Q&A with the judges. Judges will finalize their rankings and awardees will be announced that day.
For more information about the judging process, please see our FAQs page.
Our 12 Finalists:
Revealing Food Systems
- Adrienne Bowles| Cost of Inaction (COI) Calculator | Sourcemap & CIAT
- Christophe Bene | Food Systems Mapping | CIAT, LOGYCA & University of Wyoming
- Alise Dykstra & David Guerena | IVR (Interactive Voice Response) Marketing Service | VOTO Mobile & CIMMYT
- Jordania Valentim | Mapping Market Systems | ILRI, Wageningen University, GAIN & EuroMonitor
Monitoring Pests & Diseases
- Pawan Singh & T Krupnik | Disease Disruptive Data Science | UPF (Universidade de Passo Fundo) & CIMMYT
- Adam Wills | Farm.ink | ILRI
- Dave Hodson | Real Time Diagnostics for Wheat Rust | CIMMYT, EIAR, & John Innes Centre
- David Hughes & James Legg | Pest and disease monitoring by using artificial intelligence | CIAT, CIP, Bioversity International, Google, Penn State University & IITA
Disrupting Impact Assessment
- Diksha Arora |Accelerometers to measure and analyze time-use and energy expense in productive and reproductive activities | Wageningen University, University of Utah, University of Salzburg & CIAT
Empowering Data-Driven Farming
- Mona Bartling |Learning Application for Extension | CIAT, IITA & University of Salzburg
- Berber Kramer | Smartphone camera data | CABI & IFPRI
- Penelope Cabot & Julius Adewepo | Weather Information for Maize Sustainability (WIMS)| Kukua & IITA
Ref. Empower data-driven farming:
All proposals selected do not seem to advance much the Digital Agriculture agenda for scaling farmer and location-specific
and farmer specific advisory. They are in a top- to bottom order 1. Context- specific and little applicability for scaling advisory for other lower value crops 2. Approach already tried and studied in the early 2000’s- see e-Sagu in India by the Hyderabd University and Media lab , also see G.D Stone (2010): . Contradictions in the Last Mile:Suicide, Culture,and E-Agriculturei n Rural India- 3. Large number e- Extension platform provide the proposed service. The hypothesis made by the proposal have been already researched and dis proven. More comprehensive and relevant advisory is required beyond access to weather data.